Camera-based Advanced Driver Assistance Systems (ADAS) are well known, widely used mass produced machine vision systems useful for a variety of applications. Such applications may include, for example, lane departure warning, lane keeping, vehicle detection, forward collision and adaptive cruise control, and other known driver assistance applications. With advances in ADAS applications, greater demands are being placed on the modeling of radial distortion of lenses used in ADAS.
The importance of modeling lens distortion in photometry is described in Brown 1971, in which a distortion model is described (see Duane C. Brown, Close Range Camera Calibration, Photogrametric Engineering 1971). Various known methods exist for determining the radial distortion parameters of a camera after production. For example, Wang et. al. 2009 describe an efficient post-production method for calibrating the lens distortion parameters including the center of radial distortion (see Aiqi Wang, Tainshiang Qiu and Longtan Shao, A Simple Method of Radial Distortion Correction with Center of Distortion Estimation, J. Math. Imaging Vis. 2009). They use images of straight lines, and thus require a separate calibration step for each camera after production. The method of Stein (CVPR 1997) can be used to calibrate the lens distortion online using point correspondences, but this method requires non-linear optimization over four parameters (including K1, K2 and center of radial distortion) which may lead to stability problems (see Gideon P. Stein, Lens Distortion Calibration Using Point Correspondences, In Proc. CVPR 1997).
To some extent nominal lens values may be used for modeling distortion, but this may lead to inaccurate measurements since the center of radial distortion can vary considerably. One known alternative is to design lenses with minimal distortion so the lenses can be accurately modeled using the pinhole camera model. However, minimizing distortion in such designs often comes at the expense of the lens MTF, F#, size and lens price, and may lead to suboptimal performance.
Camera systems having a mechanical or electronic focus may reduce or eliminate the need for accurate focusing during manufacture. However, mechanical focus is not common in ADAS systems, where high reliability and long hours of use make mechanical systems impractical. Digital focus techniques, such as those used in some smartphone cameras, typically require high resolution and small pixel size and often fail to provide the light sensitivity desirable for ADAS. Thus, especially for cameras in ADAS, there is frequently a need for some form of lens focusing during manufacture.
It is further known that, in most cases, the camera is typically focused at infinity. However, in practice, it is generally not possible to position a focus target far enough away to give an ideal focus at infinity. A typical solution is to use a collimator lens with a target placed at a focal length corresponding to the focal length of the collimator lens. This known method generally requires a very high quality collimator lens to fill the wide FOV. This known method also generally requires precise positioning of both the target and the camera relative to the collimator. Furthermore, the lens distortion of the collimator may be compounded with the lens distortion of the camera lens, thus making it difficult to estimate the parameters for the camera lens alone.